MCP seems like a more "in-between" step until the AI models get better. I imagine in 2 years, instead of using an MCP, we will point to the tool's documentation or OpenAPI, and the AI can ingest the whole context without the middle layer.
I don't have a high opinion of MCP and the hype it's generating is ridicolous, but the problem it supposedly solves is real. If it can work as an excuse to have providers expose an API for their functionality like the article hopes, that's exciting for developers.
I don't think this is true.
My Claude Code can:
- open a browser, debug a ui, or navigate to any website
- write a script to interact with any type of accessible api
All without MCP.
Within a year I expect there to be legitimate "computer use" agents. I expect agent sdks to take over llm apis as defacto abstractions for models, and MCP will have limited use isolated to certain platforms - but with that caveat that an MCP-equipped agent performs worse than a native computer-use agent.
I mean, that’s just saying the same thing — at the end of the day, there’s are underlying deterministic systems that it uses
These are just tools Anthropic provides for you. Just like the tools a non-Anthropic service provides through their MCP server.
A community-led effort of tool creation via MCP will surely be faster and more powerful than waiting for in-house implementations.
I had similar skepticism initially, but I would recommend you dip toe in water on it before making judgement
The conversational/voice AI tech now dropping + the current LLMs + MCP/tools/functions to mix in vendor APIs and private data/services etc. really feels like a new frontier
It's not 100% but it's close enough for a lot of usecases now and going to change a lot of ways we build apps going forward
What blocked me initially was watching NDA'd demos a year or two back from a couple of big software vendors on how Agents were going to transform enterprise ... what they were showing was a complete non-starter to anyone who had worked in a corporate because of security, compliance, HR, silos etc. so I dismissed it
This MCP stuff solves that, it gives you (the enterprise) control in your own walled garden, whilst getting the gains from LLMs, voice etc. ... the sum of the parts is massive
It more likely wraps existing apps than integrates directly with them, the legacy systems becoming data or function providers (I know you've heard that before ... but so far this feels different when you work with it)
Further, there are 2 kinds of users that consume the output of software. a) humans, and b) machines.
Where LLMs shine are in the 2a usecases, ie, usecases where accuracy does not matter and humans are end-users. there are plenty of these usecases.
The problem is that LLMs are being applied to 1a, 1b usecases where there is going to be a lot of frustration.
That is the odd part. I am far from being part of that group of people. I‘m only 25, I joined the industry in 2018 as part of an training program in a large enterprise.
The odd part is, many of the promises are a bit Déjà-vu even for me. „Agents going to transform the enterprise“ and other promises do not seem that far off the promises that were made during the low code hype cycle.
Cynically, the more I look at the AI projects as an outsider, the more I think AI could fail in enterprises largely because of the same reason low code did. Organizations are made of people and people are messy, as a result the data is often equally messy.
https://layercode.com/ (https://x.com/uselayercode has demos)
Have you used the live mode on the Gemini App (or stream on AI Studio)?
I made this MCP server so that you could chat with real-time data coming from the API - https://github.com/AshwinSundar/congress_gov_mcp. I’ve actually started using it more to find out, well, what the US Congress is actually up to!
MCP is already a useless layer between AIs and APIs, using it when you don't even have GenAI is simply idiotic.
The only redeeming quality of MCP is actually that it has pushed software vendors to expose APIs to users, but just use those directly...
At work I built an LLM-based system that invoke tools. We started before MCP existed, and just used APIs (and continue to do so).
Its engineering value is nil, it only has marketing value (at best).
Anthropic wants to define another standard now btw https://www.anthropic.com/engineering/desktop-extensions
MCP is for technical users.
(Maybe read the link you sent, it has nothing to do with defining a new standard)
Isn't that what we had about 20 years ago (web 2.0) until they locked it all up (the APIs and feeds) again? ref: this video posted 18 years ago: https://www.youtube.com/watch?v=6gmP4nk0EOE
(Rewatching it in 2025, the part about "teaching the Machine" has a different connotation now.)
Maybe it's that the protocol is more universal than before, and they're opening things up more due to the current trends (AI/LLM vs web 2.0 i.e. creating site mashups for users)? If it follows the same trend then after a while it will become enshittified as well.
Another way to phrase it is that MCP normalizes individual users having access to APIs via their clients, vs the usual act of connecting two backend apps where the BE owns a service key.
Once cryptocurrency was a thing this absolutely needed to exist to protect your accounts from being depleted by a hack. (like via monthly limits firewall)
Now we need universal MCP <-> API to allow both programmatic and LLM to the same thing. (because apparently these AGI precursors arent smart enough to be trained on generic API calling and need yet another standard: MCP?)
You can already do this as long as your client has access to a HTTP MCP.
You can give the current generation of models an openAPI spec and it will know exactly what to do with it.
I doubt the middleware will disappear, it's needed to accomdate the evolving architecture of LLMs.
how would ingesting Ableton Live's documentation help Claude create tunes in it for instance?
https://blog.runreveal.com/introducing-runreveal-remote-mcp-...